{"type":"ScholarlyArticle","title":"Resource Temporal Networks: Definition and Complexity","authors":[{"name":"Philippe Laborie","slug":"philippe-laborie","given":"Philippe","family":"Laborie","affiliation":""}],"abstract":"This paper introduces the concept of Resource Temporal Network (RTN), a constraint network that subsumes both classical attributes used in A.l. Planning and capacity resources traditionally handled in Scheduling. After giving a formal definition of RTNs, we analyze their expressive power and study complexities of several fragments of the RTN framework. We show that solving an RTN is in general NP-Complete - which is not surprising given the expressivity of the framework - whereas computing a Necessary Truth Criterion is polynomial. This last result opens the door for promising algorithms to solve RTNs.","doi":null,"url":"https://ijcai.org/proceedings/2003/136","pdf":"https://ijcai.org/proceedings/2003/0136.pdf","markdown":"https://ijcai.org/proceedings/2003/136.md","bibtex":"https://ijcai.org/proceedings/2003/bibtex/136","volume":{"slug":"2003","title":"Proceedings of the Eighteenth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2003","url":"https://ijcai.org/proceedings/2003/","year":2003,"location":"Acapulco, Mexico","dates":"","editors":"Georg Gottlob","isbn":"","publisher":"International Joint Conferences on Artificial Intelligence","doi_prefix":""},"section":null,"track":"","number":136,"pages":{"first":948,"last":952},"keywords":[],"videos":[],"references":[],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}